Barrel Detection

Approaches

The following approaches have been considered:

Image Acquisition & Color Identification (#1)

Strategy

• Find orange pixels (on barrel) with (Pixels) => Red - Green => High-Pass Threshold => (Orange pixels)
• Find while pixels (on barrel) with (Pixels) => Saturation => Low-Pass Threshold => (White pixels)
• (Orange pixels) => Blob seperation => Orange stripes (Bounding Boxes)
• (Orange pixels) => Blob seperation => White stripes (Bounding Boxes)
• {Orange stripes (Bounding Boxes), White stripes (Bounding Boxes)} => Blob merging => Barrels (Bounding Boxes)

Image Acquisition & Color Identification (#2)

Strategy

• Find orange pixels (on barrel) with (Pixels) => Red - Green => High-Pass Threshold => (Orange pixels)
• Scan horizontal lines of image, starting from the bottom, and moving up. When currect scan line intersects a sufficient number of orange pixels, mark the orange segment of the line as being the bottom edge of a barrel. Once the bottom edge of a barrel is identified, ignore all pixels above the bottom edge. Continue scanning.

Progress

• I have written an experimental image filter called BarrelBlobFinder, included in ImageFilterDemo v1.2.3, that implements this algorithm. It works quite well, although it could benefit from some more calibration. --David 23:22, 19 Oct 2005 (EDT)

Distance-Map Acquistion & Shape Identification

Strategy

1. Scan distances in front of robot by some method, obtaining a distance-map.
2. Find/distinguish the "plateaus" of the graph. Mark each "plateau" as the near-edge/near-face of a barrel.

Methods to Obtain a Distance Map

1. SICK
   • Obtains a distance-map along a line projected away from the robot.
   • Easy to implement programmatically.
   • Expensive hardware. May be able to get from the CS department
2. Stereoscopic Imaging
   • Obtains a distance-map along a plane projected away from the robot.
   • Difficult to implement programmatically.
   • Requires two camcorders. Currently, we only have one.

A Note on Notation

In the above steps, items surrounded with parentheses are data. Other items are analyses or filters.